I have approximate answers and possible beliefs, in different degrees of certainty, about different things. But I'm not absolutely sure of anything and of many things I don't know anything about, such as whether it means anything to ask why we're here and what the question might mean. Richard Feynman During an interview in BBC's Horizon program (1981)

Last year, before doing the nba preseason predictions,  I told you all that I was going to get this wrong. There seemed to be significant disconnect between what people thought they know and what the numbers actually said. Not only that but I knew that as with every prediction model there was absolutely no way I was going to get everything right.

Making predictions is a thankless exercise, but I love a challenge. Shall we look at how I actually did last year?

  • An average absolute error of 6 wins. It goes down to less than 5 if I ignore the injury disasters (Minnesota, New Orleans and Philly) and the Rudy Gay trade (Memphis)
  • 23 teams finished within 8 wins of the prediction. There were 2 predictions on the high side and 5 on the low side.
  • I predicted 13 of 16 Playoff teams.
  • I predicted the finals matchup. I came within a ridiculous Ray Allen three of calling that series as well.
  • I did very well last year.

But! We're going to see if we can match and improve on that this year. You see, rather than doing every team in one post, we're going to do a detailed breakdown of all 30 NBA teams.  You'll probably agree with some of our predictions, and you'll be shocked and outraged by others, but most of all, we hope that you'll be entertained.

We wouldn't mind if you told 100 of your closest friends about it, either.

Let's go over the basics for the projections first. To get to this point I had to:

Using all that information, I'm able to model player productivity for the coming year and create a win model for each team based on the following simple equation:

TeamWins = WinsPrevious WinsLost WinsGained PlayerGrowth PosADJ


  • WinsPrevious is the expected wins for previous year (This is the games the team would have been expected to win based on their Point Margin per 48 minutes last year).
  • WinsLost are the wins lost from losing productive players (i.e. wins lost to free agency, or retirement)
  • WinsGained are the wins added to the roster. These are the wins gained through acquiring free agents or draft picks.
  • PlayerGrowth is the change in player production, either a growth or a decline. These are the wins lost or gained through rotation/minute adjustments, and the progress of Father Time, which will be beneficial to the young folks, and pretty rough on the older folks.
  • PosADJ is the size and/or position adjustment based on projected rosters.

I throw this goodness in a bowl, crank the mixer up to "puree", and generate projections for each team. One new wrinkle for this year is that I've refined my variability projection for the model. This means that I should be able to more accurately forecast the likelihood of a given win total for each team.

Now, where should we start? Well, how about the bottom? Click through to read our first preview!

Want even more information? We've got the preseason data crunched as well.

Here's how the NBA looked to use right before tip off. There are upsets and surprises to be sure, but from where?

As a public service, Arturo was kind enough to update all the rosters post Gortat trade, re-run the Sim and include the playoffs. See the results here

Oklahoma City Thunder 59 - 23 .720
Portland Trail Blazers 54 - 28 .659
Minnesota Timberwolves 40 - 42 .488
Denver Nuggets 36 - 46 .439
Utah Jazz 25 - 57 .305
San Antonio Spurs 62 - 20 .756
Houston Rockets 54 - 28 .659
Memphis Grizzlies 50 - 32 .610
Dallas Mavericks 49 - 33 .598
New Orleans Pelicans 34 - 48 .415
Los Angeles Clippers 57 - 25 .695
Golden State Warriors 51 - 31 .622
Phoenix Suns 48 - 34 .585
Sacramento Kings 28 - 54 .341
Los Angeles Lakers 27 - 55 .329
Indiana Pacers 56 - 26 .683
Chicago Bulls 48 - 34 .585
Cleveland Cavaliers 33 - 49 .402
Detroit Pistons 29 - 53 .354
Milwaukee Bucks 15 - 67 .183
Toronto Raptors 48 - 34 .585
Brooklyn Nets 44 - 38 .537
New York Knicks 37 - 45 .451
Boston Celtics 25 - 57 .305
Philadelphia 76ers 19 - 63 .232
Miami Heat 54 - 28 .659
Washington Wizards 44 - 38 .537
Charlotte Bobcats 43 - 39 .524
Atlanta Hawks 38 - 44 .463
Orlando Magic 23 - 59 .280